ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation

ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation

29 June 2023

Shuyang Sun

Andrew G. Howard

Philip H. S. Torr

Liang-Chieh Chen

Papers citing "ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation"

8 / 8 papers shown

Title
MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping Amirreza Fateh Mohammad Reza Mohammadi Mohammad Reza Jahed Motlagh ViT 61 5 0 31 Dec 2024
Progressive Token Length Scaling in Transformer Encoders for Efficient Universal Segmentation Abhishek Aich Yumin Suh S. Schulter Manmohan Chandraker 36 0 0 23 Apr 2024
PolyMaX: General Dense Prediction with Mask Transformer Xuan S. Yang Liangzhe Yuan Kimberly Wilber Astuti Sharma Xiuye Gu ... Stephanie Debats Huisheng Wang Hartwig Adam Mikhail Sirotenko Liang-Chieh Chen 21 14 0 09 Nov 2023
TubeFormer-DeepLab: Video Mask Transformer Dahun Kim Jun Xie Huiyu Wang Siyuan Qiao Qihang Yu Hong-Seok Kim Hartwig Adam In So Kweon Liang-Chieh Chen ViT MedIm 75 40 0 30 May 2022
Conditional Convolutions for Instance Segmentation Zhi Tian Chunhua Shen Hao Chen ISeg 167 596 0 12 Mar 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,214 0 17 Apr 2017
Xception: Deep Learning with Depthwise Separable Convolutions François Chollet MDE BDL PINN 201 14,190 0 07 Oct 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 279 39,083 0 01 Sep 2014